Inside Unmanned Systems

AUG-SEP 2018

Inside Unmanned Systems provides actionable business intelligence to decision-makers and influencers operating within the global UAS community. Features include analysis of key technologies, policy/regulatory developments and new product design.

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ENGINEERING. PRACTICE. POLICY.
57 August/September 2018 unmanned systems
inside
self through dark corridors looking for nuclear
radiation.
"We've built a flying vehicle that simultaneously
3-D maps and radiation maps in dark, GPS-denied
airspace," Alexis said.
This new work is part of a National Robotics
Initiative project designed to help clean up 107
legacy sites of the Manhattan Project around the
country that have been shuttered for decades.
The data these robots gather will help the U.S.
Department of Energy develop a cleanup plan for
all these contaminated sites.
For their experiments, the scientists built a
hexarotor drone weighing just 2.6 kilograms (5.7
pounds). This prototype could f ly autonomously
with the aid of a Pixhawk autopilot module for at-
titude control and an Intel NUC5i7RYH mini PC
computer to help it map its surroundings, control
its position and plan its route.
The radiation detector the scientists used on the
robot was based on a Scionix V10B10 miniature
thallium-doped cesium iodide scintillator crystal
combined with a silicon photomultiplier and a
light sensor. When gamma rays from radioactive
material strike the scintillator, it gives off light
the silicon photomultiplier can amplify enough
for the sensor to detect. All in all, the entire
radiation sensor weighed just 41 grams.
"The scintillator is a consistent model we can
trust in for years to come," Alexis said, "and
through spectroscopic analysis of the radiation,
it can not only tell the intensity of the radiation,
but the type of material that produced it, such as
cobalt, cesium or uranium."
The prototype was equipped with a stereo cam-
era, as well as LEDs to help it see in the dark,
with the LEDs synchronized to f lash in time with
the camera's shutter for the most efficient use of
light. ROVIO (Robust Visual Inertial Odometry)
software used data from the camera and an in-
ertial measurement unit (IMU) to help perform
odometry. Depth perception was achieved using
either the stereo camera or LiDAR.
"As we were carrying out this research, we
had synergy with other projects we had involv-
ing exploring mines and other subterranean en-
vironments with drones, where dust or smoke
can potentially degrade their vision," A lexis
said. "The more degraded their vision becomes,
the more we factor in uncertainty into collision
avoidance. Another way we're dealing with dust
or smoke is to work with thermal sensors that
can help the drone see past such obstacles."
Alexis and his colleagues tested their proto-
type in both a lab and a train tunnel in Nevada.
They placed radioactive samples of cesium-137 in
both sites as the robot f lew around. Their UAS
built 3-D maps of the environments, erring on
the location of the radiation sources by about 25
centimeters, "which is still reasonably accurate
enough," Alexis said.
One challenge in working in underground
environments "is that everything can look more
or less the same," Alexis said. In such parame-
ter-less environments, there are not that many
details for the mapping software to use to indi-
cate location. By working with multiple sensors,
"the aim is to give the software something it can
track," he noted.
Alexis and his colleagues have moved from
their prototy pe radiation-mapping drone to
a modif ied DJI Matrix 100. While the initial
SEEING IN
THE DARK
The University of Reno
prototype used stereo
cameras, LEDs and an
inertial measurement
unit (IMU) to help it
navigate underground.
" WE'VE BUILT A FLYING VEHICLE
THAT SIMULTANEOUSLY 3-D MAPS AND RADIATION MAPS
IN DARK, GPS-DENIED AIRSPACE."
Kostas Alexis, head of the Autonomous Robots Lab, University of Nevada-Reno
RADI
ION
CLEANUP